Annals of Botany 115: 263–273, 2015
doi:10.1093/aob/mcu244, available online at www.aob.oxfordjournals.org
Are tetraploids more successful? Floral signals, reproductive success and
floral isolation in mixed-ploidy populations of a terrestrial orchid
Karin Gross and Florian P. Schiestl*
Institute of Systematic Botany, University of Zurich, Zollikerstrasse 107, CH-8008 Zurich, Switzerland
* For correspondence. E-mail [email protected]
Received: 6 August 2014 Returned for revision: 7 October 2014 Accepted: 22 October 2014 Published electronically: 13 January 2015
Background and Aims Polyploidization, the doubling of chromosome sets, is common in angiosperms and has a
range of evolutionary consequences. Newly formed polyploid lineages are reproductively isolated from their diploid
progenitors due to triploid sterility, but also prone to extinction because compatible mating partners are rare.
Models have suggested that assortative mating and increased reproductive fitness play a key role in the successful
establishment and persistence of polyploids. However, little is known about these factors in natural mixed-ploidy
populations. This study investigated floral traits that can affect pollinator attraction and efficiency, as well as reproductive success in diploid and tetraploid Gymnadenia conopsea (Orchidaceae) plants in two natural, mixed-ploidy
populations.
Methods Ploidy levels were determined using flow cytometry, and flowering phenology and herbivory were also
assessed. Reproductive success was determined by counting fruits and viable seeds of marked plants. Pollinator-mediated floral isolation was measured using experimental arrays, with pollen flow tracked by means of staining pollinia with histological dye.
Key Results Tetraploids had larger floral displays and different floral scent bouquets than diploids, but cytotypes
differed only slightly in floral colour. Significant floral isolation was found between the two cytotypes. Flowering
phenology of the two cytotypes greatly overlapped, and herbivory did not differ between cytotypes or was lower in
tetraploids. In addition, tetraploids had higher reproductive success compared with diploids.
Conclusions The results suggest that floral isolation and increased reproductive success of polyploids may help to
explain their successful persistence in mixed-ploidy populations. These factors might even initiate transformation of
populations from pure diploid to pure tetraploid.
Key words: Floral signals, floral scent, floral morphology, floral colour, pollination, reproductive success,
polyploidization, mixed-ploidy populations, floral isolation, Gymnadenia conopsea, orchid, Orchidaceae, diploid,
tetraploid.
INTRODUCTION
Polyploidization, the duplication of the genome, is strikingly
prevalent in flowering plants, with all angiosperms having undergone at least one polyploidization (Jiao et al., 2011).
Polyploidization plays an important role in angiosperm speciation (Wood et al., 2009) and is a core type of sympatric speciation (Coyne and Orr, 2004). As triploid hybrid seeds from
crosses between diploid and tetraploid plants are less viable
than parental plants or are non-viable, and as mature triploid
plants are largely sterile due to problems in pairing/segregation
of chromosomes during meiosis, newly formed polyploids are
post-zygotically strongly reproductively isolated from their diploid progenitors (Ramsey and Schemske, 1998). This is true not
only for allopolyploidization (polyploidization as a result of interspecific hybridization), but also for the less well recognized
and less studied autopolyploidization (intraspecific genome duplication; Soltis et al., 2007). A major problem of newly formed
polyploids is that they initially occur at very low frequencies,
and thus largely lack compatible mating partners, and hence
polyploid lineages are prone to extinction as soon as they
emerge (Levin, 1975). Nevertheless, polyploids are observed in
nature, and plants with different ploidy (cytotypes) often grow
sympatrically (Husband and Schemske, 1998; Burton and
Husband, 1999; Halverson et al., 2008; Mráz et al., 2008;
Trávnı́ček et al., 2011a, b). A recent study by Mayrose et al.
(2011) suggests that the net diversification rate of recently
formed polyploids is lower than that of their diploid relatives
because of an increased extinction rate, but a thorough analysis
of a more representative data set would probably decrease the
estimate of the extinction rate (Soltis et al., 2014); another
study suggested that polyploidy led to an increase in species
richness in multiple angiosperm families (Soltis et al., 2009).
This still unsolved discrepancy has motivated studies exploring
mechanisms and factors that could explain the high prevalence
of polyploids in angiosperms.
The evolutionary success of polyploids is divided into their
formation, establishment and persistence (Thompson and
Lumaret, 1992; Parisod et al., 2010). The major mechanism of
polyploid formation is the production of unreduced gametes
(Harlan and deWet, 1975; Bretagnolle and Thompson, 1995;
C The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved.
V
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264
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
Ramsey and Schemske, 1998). Newly formed polyploids are
necessarily rare and, thus, for successful polyploid establishment, mechanisms counteracting minority cytotype exclusion
are necessary. The production of unreduced gametes (Felber,
1991; Bretagnolle and Thompson, 1995; Felber and Bever,
1997; Ramsey and Schemske, 1998) and triploids, which are often not completely sterile (Felber and Bever, 1997; Ramsey and
Schemske, 1998; Husband, 2004; Yamauchi et al., 2004), ensure recurrent formation of polyploids, thereby fostering their
establishment. Several non-mutually exclusive mechanisms
may promote within-cytotype matings and thus reduce the
wastage of gametes to the non-compatible cytotype. First, selfpollination was one of the first factors suggested to slow down
the extinction of newly formed polyploid lineages (Levin,
1975) and has been shown to be generally higher in polyploids
than in diploids (Barringer, 2007). Secondly, cytotypes are often ecologically differentiated even on small scales (FelberGirard et al., 1996; Raabová et al., 2008; Sonnleitner et al.,
2010). Thirdly, assortative mating has been predicted to have
the ability to make polyploid establishment a common scenario
(Oswald and Nuismer, 2011b). Indeed, pollinator-mediated assortative mating seems to contribute considerably to the reproductive isolation between diploids and tetraploids (Segraves
and Thompson, 1999; Husband and Sabara, 2003; Kennedy
et al., 2006). In addition, a higher relative fitness can prevent
the extinction of newly formed polyploid lineages (Felber,
1991; Rodrı́guez, 1996; Suda and Herben, 2013). Seed set in
natural populations is generally higher in polyploids (Petit
et al., 1997; Nuismer and Cunningham, 2005; Castro et al.,
2012), but see Mráz et al. (2011). Such mechanisms, which enable the establishment of polyploid lineages, may also ensure
their persistence. However, the relative importance of such
mechanisms that foster polyploid establishment and persistence
in natural, mixed-ploidy populations is still largely unknown
(but see Husband and Sabara, 2003). In a study in Chamerion
angustifolium, geographic isolation and pollinator fidelity were
the strongest reproductive barriers of five pre-zygotic and two
post-zygotic reproductive barriers investigated (Husband and
Sabara, 2003). This highlights the importance of pre-zygotic
barriers for the reproductive isolation between cytotypes.
Hence, it has been suggested that assortative mating in conjunction with the relative fitness influences the change of tetraploid
frequency (Husband and Sabara, 2003) and thus is likely to influence the evolutionary fate of polyploids. However, quantification of both assortative mating and reproductive success in
natural populations in conjunction with the study of a wide
range of floral traits possibly affecting pollinator attraction is
still lacking.
In orchids, pollinator-mediated assortative mating via floral
isolation plays an important role in the reproductive isolation
among species (Schiestl and Schlüter, 2009), and polyploidy
may have contributed to the high diversification of orchids
(Amich et al., 2007). The terrestrial orchid Gymnadenia conopsea (L.) R.Br. sensu lato (s.l.) probably contains two distinct
species, namely G. conopsea (L.) R. Br. sensu stricto (s.s.) and
G. densiflora (WAHLENB.) DIETRICH (Scacchi and de Angelis,
1989; Marhold et al., 2005; Stark et al., 2011). While G. densiflora seems to be uniformly diploid, G. conopsea s.s. is known
to vary in its ploidy level among and within populations, with
the two major cytotypes being diploid and tetraploid (Marhold
et al., 2005; Jersáková et al., 2010; Stark et al., 2011;
Trávnı́ček et al., 2011b, 2012). Polyploid G. conopsea plants
are most likely of autopolyploid origin. The only possible hybridization leading to allotetraploids similar to G. conopsea
would be between G. conpsea and G. densiflora. Scent differences are, however, more pronounced between G. conopsea
and G. densiflora than between diploid and tetraploid G. conopsea plants; in addition, internal transcribed spacer (ITS) sequences differ between the two species but not between diploid
and tetraploid G. conopsea plants (Jersáková et al., 2010).
These orchids produce nectar in a long floral spur and have a
functionally specialized pollination system, being mainly pollinated by long-tongued moths (van der Cingel, 1995; Vöth,
2000; Huber et al., 2005; Meekers et al., 2012). A recent study
has shown that floral morphology, floral signals and flowering
phenology differ not only between G. conopsea and G. densiflora, but also between diploids and tetraploids in G. conopsea
(Jersáková et al., 2010). However, reproductive-isolation mechanisms between cytotypes within the species G. conopsea are
not yet well understood. Gymnadenia conopsea is relatively
common and forms large populations in suitable habitats, making it an ideal system to study evolutionary dynamics in autopolyploids and their diploid progenitors.
In this study, we aim to investigate factors, in particular assortative mating and reproductive success, that foster the persistence of polyploids in natural mixed-ploidy populations. We
specifically asked the following questions. (1) What are the differences in floral traits between sympatric diploid and tetraploid
G. conopsea cytotypes? (2) How strong is floral isolation between cytotypes? (3) Do the two cytotypes differ in flowering
phenology, herbivory and fruiting success?
MATERIALS AND METHODS
Study species and populations
The terrestrial orchid Gymnadenia conopsea (L.) R.Br. s.s. has
a wide distribution range throughout most of Europe and parts
of Asia and mainly grows on calcareous soil, from dry meadows to marshes or fens to light forests, and from the lowland to
alpine habitats (Hess et al., 1976). In Switzerland, where we
conducted the study, it occurs throughout the country and grows
locally in high numbers. The flowering season extends from the
middle of May to the middle of August. Gymnadenia conopsea
produces a single inflorescence with approx. 15–120 flowers.
Floral colour ranges from pale pink or rarely white to dark purple. Gymnadenia conopsea has a functionally specialized pollination system with a long nectar-holding spur and mainly
diurnal and nocturnal Lepidoptera as pollinators (van der
Cingel, 1995; Vöth, 2000; Huber et al., 2005; Meekers et al.,
2012). Gymnadenia conopsea is presumably largely outcrossing
and, even though self-compatible, relies on pollinators to set
fruits (Sletvold et al., 2012). We conducted this study in
2011 and 2012 in two Swiss G. conopsea populations:
Döttingen (47 34’N, 8 16’E, 500 m a.s.l.) and Remigen
(47 31’N, 8 09’E, 570 m a.s.l.). In June each year, when most
plants fully flowered, we individually marked plants along
paths through the populations. In 2011, we counted the number
of plants within 2 m of a marked plant to estimate local plant
density.
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
Ploidy-level analysis
From each marked plant, we collected 2–6 pollinaria. We
used pollinaria because the usage of meiotically reduced plant
tissue allows assessment of the ploidy level that contributes to
the next generation. To analyse the relative ploidy levels, we
used a Cell Lab QuantaTM SC-MPL flow cytometer (Beckman
Coulter, Fullerton, Canada) equipped with a mercury arc lamp.
For sample preparation, we followed a two-step protocol (cf.
Doležel et al., 2007), using Baranyi’s (01 M citric acid, 05 %
Triton X-100; Baranyi and Greilhuber, 1995) and Otto II solution [04 M Na2HPO47H2O supplemented with 4 lg mL1
DAPI (4’, 6-diamidino-2-phenylindole); Doležel et al., 2007]
and leaf material of Phaseolus coccineus as internal standard
(IS). All pollinaria collected per individual were used, and the
detailed sample preparation and analysis was as described by
Xu et al. (2011), but runs were stopped after 8000 particles or
5 min. The ploidy of a few plants could not be determined because mould grew on the pollinaria. In the flow cytometric histograms, the pollinaria material (P) appeared in two peaks: the
first peak represented meiotically reduced germ cells, and the
second peak represented maternal tissue cells and unreduced
germ cells. To assess the relative ploidy level of an individual,
we divided the median of the first P peak by the median of the
IS peak (named the ‘P:IS ratio’ hereafter). The mean 6 s.d.
count was 81226 6 43207 nuclei for the first P peak and
135348 6 77239 nuclei for the IS peak, and the mean 6 s.d.
coefficient of variation (CV) was 454 6 130 % for the first P
peak and 630 6 144 % for the IS peak. Overall, we found
three different relative ploidy levels with a mean 6 s.d. P:IS ratio of 256 6 018, 363 6 018 and 469 6 029, respectively.
As karyological counts have revealed the smallest G. conopsea
cytotype to be diploid (2n ¼ 2x ¼ 40) (Trávnı́ček et al., 2012),
we assumed that the pollinaria with the lowest relative ploidy
were haploid produced by diploid plants. Thus, we found three
cytotypes: diploid (2x; lowest P:IS ratio), triploid (3x; medium
P:IS ratio) and tetraploid (4x; highest P:IS ratio) plants
(Table 1). Cytotypes grew intermixed especially in the population Döttingen (Supplementary Data Fig. S1).
Measurement of floral traits and phenology
When both cytotypes were in full flower, we measured display size, floral morphology, floral colour and floral scent of
marked G. conopsea plants. We quantified these traits only for
the two major cytotypes, the diploids and the tetraploids,
TABLE 1. Number of Gymnadenia conopsea plants subjected to
ploidy level analysis using flow cytometry and frequency of diploid (2x), triploid (3x) and tetraploid (4x) plants in the two study
populations, Döttingen and Remigen, in 2011 and 2012
Population
Döttingen
Remigen
Year
2011
2012
2011
2012
n
100
110
98
49
Frequency (%)
2x
3x
4x
7600
6909
6633
4694
100
545
204
000
2300
2545
3163
5306
265
because triploids were too rare to conduct multivariate statistical analyses.
We measured plant height (ground to uppermost flower) and
inflorescence length [difference between plant height and stem
length (ground to lowermost flower)] to the nearest centimetre
using a measuring tape. In addition, we counted the total number of flowers per inflorescence. We measured plant height, inflorescence length and number of flowers, hereafter
summarized under the term ‘display size’, of 195 plants in 2011
(Döttingen: n2x ¼ 76, n4x ¼ 23; Remigen: n2x ¼ 65, n4x ¼ 31)
and of 107 plants in 2012 (Döttingen: n2x ¼ 36, n4x ¼ 26;
Remigen: n2x ¼ 19, n4x ¼ 26).
To quantify floral morphology, we cut one fully open but still
fresh flower per inflorescence from 107 plants (Döttingen:
n2x ¼ 36, n4x ¼ 26; Remigen: n2x ¼ 19, n4x ¼ 26) in 2012. Due
to time constraints during fieldwork, we had to store these flowers for a few days in a fridge at 4 C. We then quantified flower
size as width and length measures of the whole flower as well
as of individual flower parts and flower shape as width to
length ratios, resulting in a total of 25 floral morphology traits
(Supplementary Data Table S1). All measurements were conducted with a 135-mm digital calliper (DigiMax, Hamm,
Germany) to the nearest 10 nm. A few flowers that were rotten
were excluded from analysis.
Morphological and physiological characteristics of the orchid
pollinaria allow their precise positioning on pollinators and
hence on conspecific stigmas (Johnson and Edwards, 2000).
Thus, pollinator-induced cross-pollination will only be possible
if the size of pollinaria, their positioning on pollinators or their
bending characteristics [after removal from the flower, pollinaria undergo a bending movement into the correct position to
touch the stigma (Johnson and Edwards, 2000)] are similar
enough. To quantify pollinaria properties in G. conopsea, we
imitated pollinaria removal by a pollinator in 52 plants
(Döttingen: n2x ¼ 16, n4x ¼ 11; Remigen: n2x ¼ 9, n4x ¼ 16) in
2012 using a wooden toothpick. We measured pollinia and pollinaria size as well as bending distances, resulting in a total of
six traits, to the nearest 10 nm with the digital calliper, and we
measured bending time using a stop watch (Supplementary
Data Table S1).
To quantify floral colour, we cut another flower from the
same plants from which the flower was cut to measure floral
morphology. A few flowers rotted and were excluded from
analysis. To quantify floral colour, we used a spectrophotometer (AvaSpec-2048 Fiber Optic Spectrometer; Avantes,
Eerbeek, The Netherlands) and a short-arc xenon lamp
(AvaLight-XE Pulsed Xenon Lamp; Avantes). We acquired the
relative spectral reflectance of the flower’s labellum [percentage of a white reference tile (Avantes)] between 300 and
700 nm. For each labellum, we measured the relative reflectance three times and then calculated the mean of these three
measurements at every nanometre. To investigate the pollinators’ view of floral colour, we adapted the colour hexagon for
bee colour vision (Chittka, 1992; Chittka and Kevan, 2005) to
the colour vision of Macroglossum stellatarum. Macroglossum
stellatarum is an important G. conopsea pollinator (Meekers
et al., 2012) with a well-studied colour vision (Kelber, 1996,
1997; Kelber and Henique, 1999). We calculated the spectral
sensitivity function of the three photoreceptors of M. stellatarum (Stavenga et al., 1993) using the maximum sensitivity
266
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
values given by Briscoe and Chittka (2001). For each plant, we
calculated the position (values of the colour hexagon x- and
y-axis) of the labellum colour, the so-called colour locus, in the
colour hexagon (Chittka and Kevan, 2005). For the calculation,
we used standard daylight illumination (D65; CIE standard
http://www.cis.rit.edu/mcsl/online/cie.php, accessed on 31
October 2012) converted to quantal units (Kelber et al., 2003)
and a standard background estimated as the mean reflectance
spectrum of leaves of 38 plant species growing in Europe
(Arnold et al., 2010). To quantify colour contrast between diploid and tetraploid plants, we calculated distances between each
pair of colour loci (Chittka, 1992).
To quantify floral scent bouquets, we collected floral scent
of intact inflorescences of 189 plants (Döttingen: n2x ¼ 73,
n4x ¼ 21; Remigen: n2x ¼ 65, n4x ¼ 30) in 2011, using headspace sorption. We performed scent collections between 0900
and 1800 h (GMT þ 1) on days without rain. Because of the relatively long time needed for scent collection, it was not possible
to collect scent at the same time for all plants. We enclosed
R
each inflorescence in an oven bag (NalophanV
) tied up with
short pieces of florist wire. We placed a small absorbent glass
tube (hereafter called the filter), which was filled with approx.
R
20 mg of 80/100 mesh TenaxV
powder (Supelco, Bellefonte,
PA, USA), inside the bag. For 30 min at a rate of
150 mL min1, a battery-operated vacuum pump (PAS-500
Micro Air Sampler; Spectrex, Redwood City, CA, USA) pulled
air out of the bag through the filter to trap the floral volatiles on
R
the TenaxV
adsorbent. To control for background contaminants, we collected ambient air from 2–3 empty bags per popuR
lation. After scent collection, we wrapped PTFE (TeflonV
)
thread sealing tape around the ends of the filters and enclosed
the whole filters in aluminium foil or small glass vials. We
stored the filters in a 30 C freezer until analysis. For sample
analysis, we used an Agilent GC 6890N gas chromatograph
[(GC) Agilent Technologies, Palo Alto, CA, USA] connected
to an Agilent MSD 5975 mass selective detector (Agilent
Technologies). The GC was equipped with an HP-5 column
(025 mm diameter, 032 lm film thickness, 30 m length) and
helium was used as carrier gas at a flow rate of 19 mL min1.
Sample injection was carried out by a thermal desorption system [(TDS) TDS3; Gerstel, Mühlheim an der Ruhr, Germany]
with a cold injection system [(CIS) CIS4; Gerstel]. We programmed the TDS temperature to rise from 30 C (05 min
hold) to 240 C (1 min hold) at 60 C min1 for thermal desorption; the CIS temperature was 150 C during thermodesorption and rose from 150 C (05 min hold) to 150 C at
16 C s1 and from 150 C to 250 C (05 min hold) at
12 C s1 for injection. The GC oven temperature was programmed to rise from 50 C to 230 C at 8 C min1. To identify compounds, the mass spectra obtained were compared with
those from the NIST spectral reference database (NIST 05)
implemented in the ChemStation Enhanced Data Analysis
program (G1701EA E.02.02 MSD Productivity ChemStation
Software; Agilent Technologies, Germany). To verify compound identification and to quantify absolute amounts of compounds, we analysed synthetic standards in one to two
concentrations to obtain calibration curves using the peak area
of a compound-specific qualifier ion. Based on these calibration
curves, the peak areas of the compound-specific qualifier ions
in the G. conopsea samples were converted into nanograms.
We manually double-checked all samples and compounds and,
if necessary, manually integrated them. For each compound, we
calculated the absolute amount in nanograms per litre of air
sampled per inflorescence. We included a compound as floral
scent compound when their median concentration in the air
controls was <80 % of their mean concentration in the plant
samples of the corresponding population. Furthermore, we considered only compounds with a mean of 05 ng L1 air sampled
per inflorescence, to exclude trace compounds. These criteria
revealed 25 floral scent compounds. For each of these compounds, we calculated the amount in nanograms per litre of air
sampled per flower by dividing the amount per inflorescence
by the number of open flowers for further analysis.
To estimate flowering phenology, we recorded the total number of flowers, the number of withered flowers, the number of
open flowers and the number of buds for each plant for which
we quantified display size (see above). We then calculated the
proportion of withered flowers, the proportion of open flowers
and the proportion of buds by dividing the number of withered
flowers, the number of open flowers and the number of buds,
respectively, by the total number of flowers.
Herbivory
The only flower-related herbivory in our G. conopsea populations was aphid infestation. Aphid load on inflorescences on a
scale from 0 (no aphids) to 5 (many aphids) was used as a measure of aphid infestation. We recorded the aphid load along
with measuring display size (see above).
Reproductive success
Between mid-July and the end of August, when plants had
fully developed fruits, we counted the number of fruits on all
marked plants. In orchids, ovaries only swell when seeds develop, making fruits easily recognizable and countable. Several
plants or labels were missing because of browsing mammalian
herbivores. We calculated relative fruiting success as the number of fruits of an individual divided by the population mean,
and the percentage fruit set as the number of fruits divided by
the total number of flowers of an individual. We cut the inflorescence with developed fruits of ten diploids, six triploids and
eight tetraploids in Döttingen in 2012. From each of these inflorescences, we randomly selected 1–3 fruits and counted viable
(well-developed embryo) and non-viable (no or shrunken embryo) seeds of a random sub-set of the thousands of seeds
encapsulated in a fruit (mean 6 s.d. ¼ 42337 6 2853 seeds per
fruit). We counted seeds at a 64 magnification under a
SZH stereo microscope (Olympus Optical Co., Ltd) equipped
with a SZH-ILLD Brightfield/Darkfield Transmitted Light
Illumination Base (Olympus Optical Co., Ltd). For each individual, we calculated the mean proportion of viable seeds.
Floral isolation experiment
To measure floral isolation between diploids and tetraploids,
we set up three experimental arrays (two in Döttingen, one in
Remigen). Each array consisted of ten diploid and ten tetraploid
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
cut plants set up in two rows with an interplant distance of
20 cm within and between rows. To track pollen flow, we
stained pollinia in a sub-set of 6–13 flowers per inflorescence
with histological dye (Peakall, 1989) using one colour per inflorescence, alternating between orange (Peakall, 1989) and pink
(Johnson et al., 2004) in diploids and between violet (van der
Niet et al., 2011) and green (Peakall, 1989) in tetraploids. All
dyes were dissolved in H2O and mixed with 133 lL mL1
Tween-20 (van der Niet et al., 2011). The staining of pollinia
does not affect pollinaria removal, bending time, and deposition
by pollinators (Peakall, 1989). The proportion of open flowers
of the experimental plants did not differ between diploids
(mean 6 s.e. ¼ 3952 6 240 %) and tetraploids (4450 6
252 %; two-sample t-test: t58 ¼ 1432, P ¼ 0158). Cut plants
were put in 15 mL BD FalconTM conical tubes filled with water,
which were placed in the ground at least 20 m apart from naturally growing G. conopsea plants; the distance between the two
arrays in Döttingen was approx. 100 m. After four sunny days,
plants were removed and the number of stigmas pollinated by
stained massulae (pollen clumps) was counted separately for
each colour using a hand lens and a binocular microscope. To
estimate the proportion of pollinator-mediated autogamy/geitonogamy, we divided the number of flowers with self-massulae
on the stigmas by the total number of flowers with stained massulae on the stigmas. As pollinators usually move from one
plant to a directly neighbouring plant (K. Gross, pers. obs.), pollinations by massulae of the same colour as the focal plant were
most likely of autogamous/geitonogamous origin and not crosspollinations from the four other plants with the same colour
within the array. Such unexpected cross-pollinations would
have led to a slight overestimation of autogamy/geitonogamy,
which, however, would have been similar for both cytotypes.
The floral isolation index was calculated for each experimental
array as 1 (observed/expected intercytotype pollen flow)/
(observed/expected intracytotype pollen flow) (Martin and
Willis, 2007; Lowry et al., 2008) with the expected intercytotype and intracytotype pollen flow being (intercytotype þ
intracytotype pollen flow)/2.
Statistical analysis
All statistical analyses were conducted in IBM SPSS
Statistics 20.0.0 (IBM Corp. 2011, Armonk, NY, USA). To
achieve normal distribution and improve homogeneity of variances, all data apart from floral morphology, floral colour,
number of fruits in 2012 and floral isolation index were log,
square root or arcsine or arcsine square root (for proportion
data) transformed. We analysed differences between cytotypes
separately for the trait groups display size, floral morphology,
pollinaria properties, floral colour and floral scent because we
did not measure all trait groups in all marked plants and in both
years. To reduce the number of variables and to account for
correlations among traits, we conducted principal component
analyses (PCAs) on traits standardized to a mean of 0 and an
s.d. of 1, separately for floral morphology, pollinaria properties
and floral scent. We extracted principal components (PCs) with
an eigenvalue >1, after varimax rotation (Supplementary Data
Table S2). Separately for the three trait groups, we conducted a
stepwise discriminant function analysis (DFA) with the
267
extracted PCs as independent variables and the cytotype/population identity as grouping variable (Table S3). We used the
stepwise procedure to assess variables most relevant for differences among groups. For entering and removing new variables,
the Wilks’ lambda method was used, which, at each step, enters
the variable that minimizes the overall Wilks’ lambda. The
probability of F was used as the criterion for entering and removing variables; a variable was entered into the model if the
significance level of its F-value was < 005 and was removed if
the significance level was >010. To quantify which differences
were explained by individual discriminant functions (DFs), we
conducted general linear models (GLMs) with the DF as dependent variable, cytotype as fixed factor and population as random factor. Similar GLMs were used to analyse differences in
individual traits, aphid load and fruiting success between cytotypes and populations. To assess differences in flowering phenology, we compared the proportion of open flowers, the
proportion of withered flowers and the proportion of buds between diploids and tetraploids with two-sample t-tests separately
for each date of collection and population. Correlations between
floral scent compounds and inflorescence length or the number
of flowers were analysed using Pearson correlations. To analyse
differences in the proportions of viable seeds, we conducted a
one-way analysis of variance (ANOVA). We analysed pairwise
differences between diploids, tetraploids and triploids with
Tukey’s post-hoc tests. The relationship between density and
reproductive success was analysed with linear regression analyses. To compare the proportion of autogamy/geitonogamy between diploid ant tetraploid plants, we used a two-sample t-test.
Similarly, we analysed differences between intracytotype and
intercytotype pollen flow with two-sample t-tests. To assess
differences between observed and expected values of floral
isolation and colour distances, we used one-sample t-tests.
RESULTS
Cytotype differences in floral traits and phenology
Most floral traits differed significantly between cytotypes, but
to a lesser extent between populations (Fig. 1; Tables 2 and 3;
Supplementary Data Table S4). Tetraploid plants had a significantly larger display size (Fig. 1A). Floral morphology also differed between cytotypes but not between populations (Fig. 1B;
Tables 2 and 3). Most ‘flower size traits’ were significantly
larger in tetraploids, but ‘floral shape traits’ did not differ between cytotypes (Table S4). Most floral morphology traits did
not differ significantly between populations (Table S4).
Pollinaria properties also differed between cytotypes, but to a
lesser extent between populations (Fig. 1C; Tables 2 and 3). In
univariate comparisons, some properties of pollinaria were significantly enhanced in tetraploids, but rarely differed between
populations (Table S4). Among floral signals, floral colour differed only slightly (Fig. 1D), but floral scent differed more
strongly (Fig. 1E) between cytotypes. The y:x ratio of the floral
colour loci (a measure of the position of the colour point in the
colour hexagon) differed significantly between cytotypes, but
not between populations; however, distances between floral
colour loci of diploids and tetraploids were significantly shorter
than 01 colour hexagon units in both populations (Fig. 1D).
Such distances are most probably too short for pollinators to be
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
B
0
60
2012
40
20
0
2x 4x
D
0
15
10
0
60
40
20
5
0
D
R
Population
−4
Spectrum locus
−1
−1
0
Colour hexagon x
1
2x
4x
0·75
0·5
0·25
0
6
0·075
4
0
−2
−2
0
2
DF1 (94·9 %)
2x
4
4x
D
2x
4x
R
2x D
4x
2x R
4x
2
0
−2
0·025
D
R
Population
0
Floral scent
0·1
0·05
2
−4
−4
DF2 (27·3 %)
Background Colour loci
1
Colour distance
2x R
4x
Colour hexagon y :x ratio
0
−2
D
R
Population
Pollinaria properties
4
0
E
2x D
4x
2x R
4x
2
20
Floral colour
1
Colour hexagon y
5
0
D
R
Population
40
10
2x D
4x
DF1 (100 %)
20
C
Floral morphology
4
60
15
Inflorescence length
Plant height
Display size
2011
2x
60
4x
40
DF2 (4·3 %)
A
Number of flowers
268
−4
D
R
Population
−6
−3
0
3
DF1 (64·3 %)
FIG. 1. Differences in floral traits between diploid (2x) and tetraploid (4x) Gymnadenia conopsea plants in the populations Döttingen (D) and Remigen (R).
(A) Picture of a diploid and tetraploid G. conopsea plant scaled to their mean height (scale bar ¼ 5 cm) and graphs (mean 6 s.e.) of display size traits (cytotype differences for all traits, P 0001; population differences, P < 0050 only for plant height in 2012 and inflorescence length and number of flowers in 2011). Multivariate
comparisons of (B) floral morphology and (C) pollinaria properties by stepwise discriminant function analyses (DFAs; for statistics, see Tables 2 and 3). (D) Colour
differences among cytotypes displayed through loci in the colour hexagon (left) adapted to the colour vision of the pollinator Macroglossum stellatarum (insert),
mean (6 s.e.) colour hexagon y:x ratio (middle; cytotype difference, P ¼ 0019; population difference, P ¼ 0474), and colour distance between diploid and tetraploid
colour loci in relation to the presumed detection threshold (horizontal line) (right; always P < 0001). (E) Multivariate comparison of floral scent bouquets through
stepwise DFA (for statistics, see Tables 2 and 3). For all DFA plots, percentages of variance explained by specific DFs are indicated in parentheses.
TABLE 2. Statistics of stepwise discriminant function analyses
(DFAs) with cytotype population identity as grouping variable
for the three trait groups floral morphology, pollinaria properties
and floral scent
Trait group
Floral morphology
Pollinaria properties
Floral scent
Test of functions
Wilks’ k
v2
d.f.
P
DF1–DF3
DF2–DF3
DF3
DF1
DF1–DF3
DF2–DF3
DF3
0231
0869
0979
0495
0272
0584
0869
134980
12868
1971
34070
238845
98544
25702
12
6
2
3
15
8
3
<0001
0045
0373
<0001
<0001
<0001
<0001
Significant separations by discriminant functions (DFs; for details, see
Supplementary Data Table S3) are highlighted in bold.
able to discriminate them (Chittka et al., 2001). Multivariate
comparisons of floral scent bouquets showed that cytotypes
differed in their scent bouquet (Fig. 1E; Tables 2 and 3).
Populations showed significant but weaker differences in scent
bouquet (Fig. 1E; Tables 2 and 3). While total scent amount
and total amount of aromatics were significantly lower in tetraploids, other scent compounds were significantly more abundant in tetraploids (Table S4). The emission of several floral
scent compounds correlated negatively with inflorescence
length and, to a lesser extent, with the number of flowers
TABLE 3. General linear model (GLM) statistics of cytotype and
population differences in the discriminant functions (DFs) resulting from stepwise discriminant function analyses (DFAs; for details, see Supplementary Data Table S3)
Trait
Cytotype
F*
Floral morphology
DF1
23700
DF2
010
DF3
004
Pollinaria properties
DF1
3573
Floral scent
DF1
20210
DF2
304
DF3
036
Population
P
F*
P
<0001
0753
0840
048
270
152
0490
0104
0221
<0001
451
0039
<0001
0082
0549
1807
8232
004
<0001
<0001
0838
Significant differences are highlighted in bold.
*Degrees of freedom: floral morphology, 1,94; pollinaria properties, 1,49;
floral scent, 1,186.
(Table S5). The amounts of some scent compounds also differed significantly between populations (Table S4).
Differences in the proportion of open flowers, the proportion
of withered flowers and the proportion of buds between diploids and tetraploids were not always significant, and these differences tended to be less pronounced at later flowering dates,
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
0
2012
40
0
2
0
D
R
0
B
100
50
1
20
0
50
1
Proportion of viable
seeds
Number of fruits
20
60
2
Percentage fruit set
40
100
2x
3x
4x
Relative fruiting success
A 60 2011
269
D
0
R
D
1
0
R
2012
D
FIG. 2. Differences (mean 6 s.e.) in reproductive success between diploid (2x), triploid (3x) and tetraploid (4x) Gymnadenia conopsea plants in the populations
Döttingen (D) and Remigen (R) in 2011 (upper) and 2012 (lower). (A) Three measures of fruiting success (differences between 2x and 4x, always P < 005; differences between 2x and 3x as well as between 3x and 4x, always P > 005; population differences, P < 005 only for relative fruiting success in 2012). (B) Proportion
of viable seeds (difference between 2x and 4x, P ¼ 0785; difference between 2x and 3x as well as between 3x and 4x, P < 0001).
especially for the proportion of withered flowers and the proportion of buds (Supplementary Data Fig. S2). This indicates
that the flowering phenology of diploids and tetraploids greatly
overlapped.
Cytotype differences in herbivory
The extent of aphid infestation was significantly higher in
diploids than in tetraploids in 2011, but not in 2012
(Supplementary Data Fig. S3). Similarly, there was a difference
in the aphid load between populations in 2011, but not in 2012
(Fig. S3).
TABLE 4. Mean 6 s.e. and statistics for differences between intracytotype and intercytotype pollen flow for diploid (2x) and tetraploid (4x) Gymnadenia conopsea plants and for both cytotypes
combined (overall)
Ploidy
level
2x
4x
Overall
Mean 6 s.e.
Intracytotype
pollen flow
Intercytotype
pollen flow
063 6 049
197 6 023
130 6 033
010 6 000
053 6 030
032 6 015
Statistics
d.f.
t
P
2
2
2
1086
4300
4005
0391
0050
0057
Significant differences determined using two-sample t-tests are highlighted
in bold.
Cytotype differences in reproductive success
Reproductive success was always significantly higher in tetraploids, but in most cases did not differ between populations
(Fig. 2). In both years, tetraploids produced more fruits and had
a higher relative fruiting success and percentage fruit set than
diploids (Fig. 2A). Fruiting success did not differ between triploids and either diploids or tetraploids (Fig. 2A). However, triploids had significantly lower proportions of viable seeds than
diploids and tetraploids, but there was no difference in viable
seeds between diploids and tetraploids (Fig. 2B). Relative fruiting success and percentage fruit set increased significantly with
local density only in diploids in Remigen. In tetraploids and in
Döttingen, there was no significant association between density
and reproductive success (Supplementary Data Table S6).
Floral isolation
Significantly more stigmas were pollinated by colour-stained
pollinia in tetraploids than in diploids, indicating that tetraploids were visited more or had a higher pollination efficiency
(mean 6 s.e.; tetraploids, 250 6 039; diploids, 073 6 029;
t58 ¼ 4656, P < 0001). The proportion of autogamy/geitonogamy was similar between the cytotypes (mean 6 s.e. diploids, 048 6 015; tetraploids, 051 6 008; t32 ¼ 0202,
P ¼ 0841). There was more pollen flow within than among
cytotypes, but this difference was only significant for tetraploids (Table 4). The mean 6 s.e. floral isolation index was
076 6 008, which was significantly higher than 0, i.e. random
visitation (t2 ¼ 9268, P ¼ 0011).
DISCUSSION
Polyploidy is a common phenomenon in plants, and autopolyploids often co-occur with their diploid progenitors (Thompson
et al., 1997; Husband and Schemske, 1998; Burton and
Husband, 1999; Halverson et al., 2008; Trávnı́ček et al.,
2011b). However, factors influencing the evolutionary fate of
polyploids in such natural mixed-ploidy populations have remained largely unknown. In our study, we confirmed consistent
270
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
phenotypic differences between diploid and tetraploid orchid
individuals, not only in plant and flower morphology, but also
in floral scent. Most probably as a consequence of these differences, tetraploids achieve mostly within-cytotype pollen flow
and have higher pollination success. Assuming similar figures
of survival for both cytotypes, higher reproductive success and
assortative mating will probably allow polyploids to persist in
mixed-ploidy populations or even displace their diploid
progenitors.
It is well known that (auto)tetraploid plants are larger and
bear larger flowers than their diploid progenitors (Levin, 1983;
Segraves and Thompson, 1999; Husband and Schemske, 2000;
Hodálová et al., 2010; Münzbergová et al., 2013), with rare exceptions (Ståhlberg, 2009), but few studies have investigated
how floral signals differ between cytotypes. Floral colour,
when measured as binary character or as percentage reflectance, differs between cytotypes in Centaurea stoebe (Mráz
et al., 2011) and Heuchera grossulariifolia (Segraves and
Thompson, 1999), but has been reported to be very similar in
different cytotypes in a previous study in G. conopsea
(Jersáková et al., 2010). In our study, we showed that although
colour differed statistically among cytotypes, this difference is
unlikely to be detectable for pollinators. Floral colour distances
between cytotypes were <01 colour hexagon unit, suggesting
a lack of colour discrimination (Chittka et al., 2001). Floral
scent has, until now, only been studied once in diploids and
polyploids of the same plant species (Jersáková et al., 2010),
despite its importance for pollinator attraction and floral isolation (Raguso, 2008; Schiestl and Schlüter, 2009). In our study,
we analysed a large number of plants and found that floral scent
bouquets differed between cytotypes, which is consistent with
an earlier study in G. conopsea (Jersáková et al., 2010). In addition to analysing the floral bouquet, we also assessed differences in individual compounds. Unexpectedly, individual scent
compounds were not always emitted in higher amounts in tetraploids, but the amount of several compounds as well as the total
amount of scent were lower in tetraploids. This lower scent
emission is likely to be caused by a trade-off between inflorescence size and floral scent production. In tetraploids, but not in
diploids, a negative correlation between size and floral
scent was evident for the sum of aromatic compounds and the
individual compound phenylacetaldehyde in particular.
Interestingly, an earlier study showed that the amount of phenylacetaldehyde is important in mediating floral isolation between two Silene species (Waelti et al., 2008). Thus, a trade-off
between display size and key floral volatiles may indirectly impact pollinator attraction and floral constancy of pollinators by
altering the combination of visual and key olfactory signals. In
our study, the observed phenotypic differences could be the
direct consequence of the genome duplication itself (Griesbach
and Kamo, 1996; Ramsey and Schemske, 2002; Oswald and
Nuismer, 2011a; Ramsey, 2011) or secondarily caused by divergent natural selection (Nuismer and Cunningham, 2005).
Modelling studies suggest that higher relative reproductive
success and assortative mating are key factors for tetraploids to
become successfully established and persist in mixed-ploidy
populations (Rodrı́guez, 1996; Oswald and Nuismer, 2011b;
Suda and Herben, 2013). Higher reproductive fitness of tetraploids compared with diploids enables tetraploids to become
more common (Felber, 1991; Rodrı́guez, 1996; Rausch and
Morgan, 2005; Suda and Herben, 2013). In our study, fruiting
success was considerably higher in tetraploid than in diploid
plants, which is consistent with earlier studies (Petit et al.,
1997; Nuismer and Cunningham, 2005; Castro et al., 2012), but
see Mráz et al. (2011). Assortative mating (i.e. intracytotype
pollen flow) reduces the loss of male gametes to non-compatible
cytotypes and ensures the inflow of compatible pollen (Levin,
1975), as matings between diploids and tetraploids usually lead
to sterile offspring. In line with previous findings (Burton and
Husband, 2000; Baack, 2005; Borges et al., 2012), post-zygotic
isolation was strong between G. conopsea cytotypes, with
the few occurring triploid hybrids being largely sterile. We observed assortative mating both in terms of pollinator-mediated
autogamy/geitonogamy and through assortative pollinator
visitation, collectively leading to considerable floral isolation
between the two cytotypes. The strength of the here documented
floral isolation is comparable with that between
C. angustifolium cytotypes (Husband and Schemske, 2000;
Husband and Sabara, 2003; Kennedy et al., 2006), but much
stronger than that between Aster amellus cytotypes (Castro
et al., 2011). Floral isolation might be caused by a switch to
new pollinators after polyploidization as in H. grossulariifolia
(Segraves and Thompson, 1999; Thompson and Merg, 2008).
More probably, however, floral isolation in G. conopsea was
caused by the pollinators’ preference for floral signals of tetraploid plants, as shown in C. angustifolium (Husband and
Schemske, 2000; Kennedy et al., 2006). In our plot arrays, tetraploids had higher pollination success than diploids, despite both
cytotypes being in full flower and surviving during the plot experiment equally well. Morphological isolation and differences
in pollination efficiency between the two cytotypes seem to
be weak or absent, because differences in traits mediating morphological isolation (pollinaria and stigma properties) were
generally less pronounced than differences in other floral traits.
Moreover, spur length differences were <2 mm and thus also
unlikely to cause mechanical isolation or differences in pollination efficiency (Jersáková et al., 2010). Tetraploids also did not
show more pollinator-mediated autogamy/geitonogamy than
diploids. Thus, even though detailed pollinator observations
and behavioural experiments would be necessary to assess
pollinator preferences, our study implies that the increased display size and/or changes in the floral scent bouquet in tetraploid
G. conopsea plants most probably lead to higher reproductive
success, as well as assortative pollen flow mostly within
cytotypes.
Floral isolation and higher reproductive success in tetraploids
suggests that tetraploids can displace diploids, leading to transformation of G. conopsea populations from pure diploid to pure
tetraploid. Indeed, we found one population with only tetraploid
and no diploid plants in Switzerland (K. Gross, unpubl. data),
where such a transformation may have taken place. Several factors, however, can slow down or even prohibit such a transformation. First, high inbreeding depression may restrict tetraploid
persistence and diploid displacement (Rausch and Morgan,
2005). In G. conopsea, inbreeding depression can be strong
(Sletvold et al., 2012), but inbreeding depression has been
shown to be generally lower in polyploids than in diploids
(Barringer and Geber, 2008). Secondly, as an alternative to
transformation, cytotypes may diverge into two species, mediated by an adaptive shift in flowering phenology (Husband and
Gross & Schiestl — Reproductive success and floral isolation in mixed-ploidy populations
Schemske, 2000; Thompson and Merg, 2008; Castro et al.,
2011) or (micro-)habitat (Felber-Girard et al., 1996;
Schönswetter et al., 2007; Raabová et al., 2008; Sonnleitner
et al., 2010). Indeed, spatial clustering of cytotypes and flowering time shifts were found in populations with different cytotypes of G. conopsea in the Czech Republic (Jersáková et al.,
2010; Trávnı́ček et al., 2011b), suggesting adaptation to different flowering time niches and/or microhabitat. In our study,
even though a slight spatial clustering of cytotypes was recognizable, different cytotypes were clearly still within flying distances of foraging pollinators (K. Gross, pers. obs.), and
flowering phenology was only slightly advanced in diploids
compared with tetraploids. Thus, whether polyploidization
leads to transformation or divergence seems to be population or
region specific. Finally, the success of tetraploids may be compromised by lower survival, for example mediated by lower
competitive abilities or seedling establishment, selective herbivore grazing or mowing, or lower resistance against pathogens.
However, competitive abilities (Levin, 1983), germination rate
and seedling survival (Burton and Husband, 2000; Mráz et al.,
2012) do not differ between cytotypes in other plant species.
Several studies investigated the effect of ploidy on herbivore
attack (Thompson et al., 1997; Nuismer and Thompson, 2001;
Thompson et al., 2004; Halverson et al., 2008; Arvanitis et al.,
2010). The only observed herbivores in our G. conopsea populations were aphids, but aphid load did not differ between cytotypes or was even lower in tetraploids. Collectively, factors
acting on survival may have little effect on the process of cytotype displacement in G. conopsea, but more studies on differential survival of cytotypes are needed to confirm this.
Our data suggest that tetraploids are very successful in contemporary populations; though this may not necessarily be the
case during establishment, when teraploids occur in very low
frequencies. In theory, low frequency may decrease floral isolation and reproductive success, but a study in C. angustifolium
showed that the proportion of intracytotype pollinator visits did
not depend on cytotype frequency in diploids and was highest
at low tetraploid frequencies in tetraploids (Husband, 2000). In
support of this, our study shows that reproductive success of tetraploids was not generally density dependent, and, thus, even
rare and/or isolated tetraploids had high reproductive success.
Thus, floral isolation and reproductive success might also be
high for tetraploids during the establishment phase, but only if
the trait differences causing high reproductive success are directly caused by polyploidization. Thus, future experimental
studies should investigate which of the here documented differences in floral traits are directly caused by polyploidization,
and quantify reproductive success as well as floral isolation at
low tetraploid frequencies, to learn more about these key factors during polyploidy establishment.
SUPPLEMENTARY DATA
Supplementary data are available online at www.aob.oxfordjournals.org and consist of the following. Figure S1: cytotype
distribution in the two study populations. Figure S2: cytotype
differences in flowering phenology. Figure S3: cytotype differences in aphid load. Table S1: description of floral morphology
traits and pollinaria properties. Table S2: factor loadings on
271
principal components. Table S3: factor loadings on discriminant functions. Table S4: cytotype and population differences
in floral morphology, pollinaria properties and floral scent compounds. Table S5: Pearson correlation coefficients of floral
scent compounds and inflorescence length and number of flowers. Table S6: regression coefficients for local density on fruiting success.
ACKNOWLEDGEMENTS
We thank M. Sun for help in the field, E. C. Connor for help
in the field and with scent analysis, C. Sailer for introduction
to and kind support with flow cytometry, K. E. M. Sedeek for
the preparation of the histological dyes, and M. Streinzer for
helpful comments on floral colour analysis. Two anonymous
reviewers provided helpful comments on the manuscript. The
‘Departement Bau, Verkehr und Umwelt; Abteilung
Landschaft und Gewässer; Sektion Natur und Landschaft’
from Kanton Aargau, Switzerland provided collection permissions. We are also grateful to U. Somalvico from creaNatira
for organizing the fencing of our plants in Remigen to protect
them from cows. Financial support for this study was provided
by the Swiss National Science Foundation grant 31003A125340 to F.P.S.
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